Complex, adaptive behavior in animals is likely to be a result of the coupling between neural network controllers and a nonlinear periphery. In order to test this hypothesis, we propose to study a neural network, the periphery which it controls, and their interactions in a technically approachable system, to model and simulate this system in order to understand its normal function, and to predict the effects of perturbations (e.g., random changes in load and muscle lesions) on the function of the system. Specifically, we propose to study the neural network and musculature which mediate feeding behavior in the marine mollusc Aplysia. We will analyze the functional anatomy of the feeding apparatus of the animal, the buccal mass, which is similar to the tongue of higher animals both in its mechanisms of action and degrees of freedom. We will also identify motor neurons and proprioceptors responsible for the control of the buccal mass. These data will form the basis of a detailed mathematical model and computer simulation of the buccal mass and its neural control. The model will be used to predict the normal function of the system, and the effects of lesions and other perturbations on the system, which will then be tested experimentally. These studies will contribute to an understanding of the interactions between the central nervous system and the periphery. Such an understanding may explain the way in which motor systems make use of excess degrees of freedom for multifunctionality, and their robustness in the face of damage or disease, These studies can serve as a basis for understanding motor control of quasi-rhythmic behavior in more complex animals, such as respiration in higher vertebrates.